The role of a Data Scientist is changing. Skills in R, Python, SQL, Hadoop etc. are no longer enough to stay competitive on the market.
With more and more interest in Data Science as a career choice, the competitiveness in the market is only set to increase. To stay ahead of the competition, it is vital to prioritise your professional development or risk being surpassed by a workforce with a more diverse skillset.
This can be quite daunting as there are a vast array of software, frameworks and languages that are relevant to data science and while making this decision depends on your current role or desired career path, there are some skills that are becoming generally more desirable across the whole industry.
So if you have committed to self-improvement in 2020, then the following three skills could be a great place for you to start.
Cloud Computing is fast becoming one of the most sought after skills in 2020. Apart from various skills which a data scientist must possess like analysis, statistics and programming, you are also expected to work on newer platforms in which the organization stores data.
Where Data Scientists can work on reducing the time needed by a model, the IT people can contribute by changing to faster computing services which are generally obtained through cloud computing amongst other things.
Moving from computing resources to external vendors like AWS, Microsoft Azure or Google Cloud makes it very easy to set up a very fast Machine Learning environment that can be accessed from distance.
Therefore, Data Scientists must have a basic understanding of Cloud functioning. For example: working with servers at distance instead of your own computer or working on Linux rather than on Windows/Mac.
Already widely used by development teams, Agile is a way of organising work. More and more, Data Scientists and Machine Learning Engineers are managed as developers who continuously make improvements to Machine Learning elements in an existing codebase.
For this type of role, Data Scientists have to know the Agile way of working based on the Scrum method. It defines several roles for different people. This role definition makes sure that continuous improvement and be implemented smoothly.
NLP, Neural Networks and Deep Learning
Up until recently, the majority of Data Scientists considered skills in NLP and image recognition as not entirely necessary. However, with everyday use cases on the rise, this is a perception fast on the decline.
Even if there is no direct application of such models in your current role, we recommend taking on a hands-on project which is easy to find and will allow you to understand the steps needed in image and text projects.
These are our recommendations for 2020! Did we miss any?